A step of extracting components of one or more frequency bands from a first section of an EEG; a step of calculating a first index for each of the components of one or more frequency bands, wherein the first index is calculated based on a degree to which a magnitude of each of the components of one or more frequency bands with respect to a magnitude of a predetermined reference component in the first section exceeds a predetermined threshold value; a step of calculating a probability value for each of one or more patient statuses from the first index for each of the components of one or more frequency bands using a trained artificial neural network; and a step of determining the consciousness level of the patient based on the probability value for each of the one or more calculated patient statuses.

A method for visualizing data from electrical source imaging (ESI) is disclosed herein. The method converts the ESI into a plurality of ESI waveforms. The method generates a virtual electrode from the plurality of ESI waveforms. The method places the virtual electrode at a three-dimensional (3D) location of a representation of the patient's brain or on the surface of the scalp. The method receives a direct measurement of the virtual electrode at the 3D location.

A method for visualizing data from electrical source imaging (ESI) is disclosed herein. The method converts the ESI into a plurality of ESI waveforms. The method generates a virtual electrode from the plurality of ESI waveforms. The method places the virtual electrode at a three-dimensional (3D) location of a representation of the patient's brain or on the surface of the scalp. The method receives a direct measurement of the virtual electrode at the 3D location.

Provided are methods and systems of encoding and decoding speech from a subject using articulatory physiology. Methods of the present disclosure include receiving a physiological feature signal associated with a spatiotemporal movement of a vocal tract articulator, generating a speech pattern signal in response to the physiological feature signal, and outputting speech that is based on the speech pattern signal. Methods of the present disclosure further include acquiring one or more of a linguistic signal and an acoustic signal; associating a physiological feature with the linguistic or acoustic signal; generating a speech pattern signal in response to the physiological feature; and outputting speech that is based on the speech pattern signal. Speech decoding systems and devices using articulatory physiology for practicing the subject methods are also provided. Various steps and aspects of the methods will now be described in greater detail below.

Provided are methods and systems of encoding and decoding speech from a subject using articulatory physiology. Methods of the present disclosure include receiving a physiological feature signal associated with a spatiotemporal movement of a vocal tract articulator, generating a speech pattern signal in response to the physiological feature signal, and outputting speech that is based on the speech pattern signal. Methods of the present disclosure further include acquiring one or more of a linguistic signal and an acoustic signal; associating a physiological feature with the linguistic or acoustic signal; generating a speech pattern signal in response to the physiological feature; and outputting speech that is based on the speech pattern signal. Speech decoding systems and devices using articulatory physiology for practicing the subject methods are also provided. Various steps and aspects of the methods will now be described in greater detail below.

This invention relates to a wearable networking and activity monitoring device. According to the invention there is provided a wearable networking and activity monitoring device comprising a wearable garment, electronic circuitry comprising at least one conductive member integrally formed with the wearable garment and a network router attached to the garment, the network router configured to operatively broadcast a wireless local area network around the garment enabling a user to connect multiple mobile devices to the Internet via the wireless local area network. The wearable networking and activity monitoring device further comprising a power supply means, which is electrically coupled to the mobile network router through the electronic circuitry and allows the user of the garment to charge the mobile device, and an activity monitoring device embedded in the garment and operable to monitor activity and physiological information of the user.

This invention relates to a wearable networking and activity monitoring device. According to the invention there is provided a wearable networking and activity monitoring device comprising a wearable garment, electronic circuitry comprising at least one conductive member integrally formed with the wearable garment and a network router attached to the garment, the network router configured to operatively broadcast a wireless local area network around the garment enabling a user to connect multiple mobile devices to the Internet via the wireless local area network. The wearable networking and activity monitoring device further comprising a power supply means, which is electrically coupled to the mobile network router through the electronic circuitry and allows the user of the garment to charge the mobile device, and an activity monitoring device embedded in the garment and operable to monitor activity and physiological information of the user.

A system for nourishment refinement using psychiatric markers includes a computing device designed and configured to retrieve a psychiatric marker relating to a user, identify a nutrient variation as a function of the psychiatric marker, establish nourishment possibilities as a function of the nutrient variation, and generate a nourishment program, wherein generating further includes training a machine learning process as a function of a training set relating psychiatric markers and nutrient variations to nourishment programs, and generating the nourishment program as a function of the psychiatric marker, the nourishment possibilities, and the machine-learning process.

Monitoring devices and monitoring technology are disclosed for a number of applications. A monitoring device that attaches to a measurement site includes at least one of an optical sensor, a temperature sensor, or first and second electrical contact sensors. A monitoring device or a smart garment can be powered by one or more bio-batteries that is each formed by electrodes in contact with the user's body (e.g., skin) or an animal. Various method and algorithms can be used to process signals received from the optical sensor, a temperature sensor, and/or first and second electrical contact sensors. The signals received from the optical sensor, a temperature sensor, and/or first and second electrical contact sensors can be transmitted to a host device. An application program on a host device can process the signals to compute one or more physiological parameters, waveform data, trend data, and/or one or more reports.

Systems and/or methods for assessing the sleep quality of a patient in a sleep session are provided. Data is collected from the patient and/or physician including, for example, sleep session data in the form of one or more physiological parameters of the patient indicative of the patient's sleep quality during the sleep session, a subjective evaluation of sleep quality, etc.; patient profile data; etc. A sleep quality index algorithm, which optionally may be an adaptive algorithm, is applied, taking into account some or all of the collected data. Sleep quality data may be presented to at least the patient, and it may be displayed in any suitable format (e.g., a format useful for the patient to be appraised on the progress of the treatment, a format useful for a sleep clinician to monitor progress and/or assess the effectiveness of differing treatment regimens, etc).